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  2. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    A dataset for NLP and climate change media researchers The dataset is made up of a number of data artifacts (JSON, JSONL & CSV text files & SQLite database) Climate news DB, Project's GitHub repository [394] ADGEfficiency Climatext Climatext is a dataset for sentence-based climate change topic detection. HF dataset [395] University of Zurich ...

  3. Housing bubble - Wikipedia

    en.wikipedia.org/wiki/Housing_bubble

    Real housing prices vs. demography. If there is a net inflow of tenants the cost of dwelling can be expected to increase (Englund, 2011). [15] Housing prices vs. GDP can be used if data on income is unavailable, since changes in GDP and income can be expected to correlate (Claussen, Jonsson, & Lagerwall, 2011). [16]

  4. Real estate economics - Wikipedia

    en.wikipedia.org/wiki/Real_estate_economics

    Real estate economists analyze supply, demand, and pricing in real estate. Real estate economics is the application of economic techniques to real estate markets.It aims to describe and predict economic patterns of supply and demand.

  5. I’m an Economist: Here’s My Prediction for the Housing Market ...

    www.aol.com/m-economist-prediction-housing...

    I’m an Economist: Here’s My Prediction for the Housing Market Under Trump’s Next Presidency

  6. Median multiple - Wikipedia

    en.wikipedia.org/wiki/Median_Multiple

    The Median house price to income ratio was the primary indicator H1 of the 1991 World Bank/UNCHS Housing Indicator system. [ 2 ] [ 3 ] It was subsequently used as a measure of affordability by the UN Commission for Sustainable Development, the National Association of Realtors , State of the Environment 2003 Tasmania, and the Mortgage Guide UK.

  7. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  8. Kaggle - Wikipedia

    en.wikipedia.org/wiki/Kaggle

    Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.

  9. 2000s United States housing market correction - Wikipedia

    en.wikipedia.org/wiki/2000s_United_States...

    The White House Council of Economic Advisers lowered its forecast for U.S. economic growth in 2008 from 3.1 per cent to 2.7 per cent and forecast higher unemployment, reflecting the turmoil in the credit and residential real-estate markets. The Bush administration economic advisers also revised their unemployment outlook and predicted the ...